class_docstr: Proportional Prioritized Experience Replay.
      
class_docstr_tok: ["Proportional","Prioritized","Experience","Replay","."]
code: def update(self, indices, priorities):
      priorities = np.array(priorities) + self.eps
      priorities_alpha = np.power(priorities, self.alpha)
      for idx, priority in zip(indices, priorities_alpha):
          self.elements.update(idx, priority)
          self._max_priority = max(priority, self._max_priority)
  
file_path: PARL/benchmark/fluid/Prioritized_DQN/proportional_per.py
imports: import numpy
label_desc: Use image node_id 4 for calling the ProportionalPER obj's underlying member method code with example usage: obj.update(indices, priorities) without return types